Import Spreadsheet to Looker

5 min read
Connect spreadsheets to Looker with a streamlined import process for analytics-ready data.

How to Import Spreadsheet Data into Looker Using CSVBox

Integrating spreadsheet uploads into a Looker-powered analytics stack can be challenging—but the right tools make it seamless. Whether you’re building a SaaS platform, managing a low-code product, or leading data infrastructure for a startup, this guide shows you how to efficiently go from Excel or CSV to Looker dashboards with minimal friction.

Why This Matters

Many business users still rely heavily on spreadsheets—storing everything from customer data and KPIs to campaign metrics and sales forecasts. If your application or team depends on Looker for BI, it’s essential to bridge the gap between user-uploaded spreadsheets and your Looker models.

The problem? Looker doesn’t support direct spreadsheet uploads. The solution? Use a secure, scalable importer like CSVBox to load spreadsheets into a connected data warehouse Looker can query.

Overview: Steps to Connect Spreadsheet Uploads to Looker

Here’s a step-by-step breakdown to help technical teams implement spreadsheet ingestion into Looker using CSVBox:

1. Understand Looker’s Data Model

Looker doesn’t store data—it queries it live from external sources such as:

  • Google BigQuery
  • Amazon Redshift
  • Snowflake
  • PostgreSQL
  • MySQL

💡 Goal: Upload spreadsheet data into one of those sources, then model it in Looker.

2. Set Up a Destination Database

Pick a connected database that Looker can read from. You’ll need:

  • Active connection in Looker (with appropriate credentials)
  • A target table for storing user-uploaded data

Example:

  • sales_data table in BigQuery
  • customer_onboarding_data table in Snowflake

✅ Make sure your data warehouse allows write access from your app/backend.

3. Use CSVBox to Enable Spreadsheet Upload

CSVBox lets you add a ready-made import button inside your web app or admin portal—making it simple for users to upload CSV or Excel files.

Steps:

  1. Sign up at CSVBox
  2. Create a new Importer
  3. Define the expected data schema (fields, validations, format)
  4. Integrate the CSVBox widget in your frontend

Example integration:

<script src="https://unpkg.com/csvbox"></script>

<button id="csvbox-launch">Import Spreadsheet</button>

<script>
  CSVBox.init({
    user: { email: "[email protected]" },
    licenseKey: "YOUR_CSVBOX_LICENSE_KEY",
    onImportComplete: function (data) {
      // Send rows to backend or database
      console.log(data);
    }
  });

  document.getElementById('csvbox-launch').addEventListener('click', CSVBox.launch);
</script>

📘 More on installation: CSVBox Install Guide

4. Move Uploaded Data into Your Database

After upload, CSVBox gives you validated, structured spreadsheet rows. You can POST this to your own backend, then insert into your database.

Example using Node.js:

app.post('/upload', async (req, res) => {
  const rows = req.body.data; // array of cleaned rows
  await db.batchInsert('sales_data', rows); // use your DB library
  res.status(200).json({ status: 'success' });
});

✅ Sanitize inputs and handle duplicates or schema mismatches here.

5. Define LookML to Model the Data

Once the spreadsheet data lives in your warehouse, create a LookML model to expose it in Looker:

view: sales_data {
  sql_table_name: sales_data ;;

  dimension: customer_name {
    type: string
    sql: ${TABLE}.customer_name ;;
  }

  measure: total_sales {
    type: sum
    sql: ${TABLE}.amount ;;
  }
}

Now the imported spreadsheet data can be used in dashboards, visualizations, and explorable reports.

Common Pitfalls (and How to Prevent Them)

Here are the most frequent issues developers run into when implementing spreadsheet-to-Looker pipelines:

⚠️ 1. Unsupported File Types

  • CSVBox supports both .csv and .xlsx
  • Define schema & required fields via dashboard to disallow invalid uploads

⚠️ 2. Column/Data Type Mismatches

  • Ensure frontend and database schema match
  • CSVBox helps with field-level validations (e.g., dates, emails, numbers)

⚠️ 3. Duplicate Records

  • Use upsert logic in your backend rather than blind inserts
  • Compare unique identifiers if present in each upload

⚠️ 4. Large File Uploads

  • Chunk uploads server-side
  • Use CSVBox’s webhook to process data upon completion

⚠️ 5. Out-of-Sync Data in Looker

  • Looker can cache queries—use persistent derived tables (PDTs) when needed
  • Control freshness with persist_for settings or refetch intervals

Why Use CSVBox?

Creating your own spreadsheet parser and validation logic from scratch is time-consuming and error-prone. CSVBox solves that with:

🎯 Features Built for Dev Teams & Data Products

  • ✅ Secure spreadsheet ingestion (CSV & XLSX)
  • ✅ Real-time field validation in-browser
  • ✅ No need to manually parse, map, or sanitize files
  • ✅ User-friendly UI customizable to your brand
  • ✅ Upload-progress tracking and error reporting
  • ✅ Direct integrations to databases (BigQuery, Redshift, Snowflake, etc.)

🔎 Ideal for:

  • User onboarding flows with customer data
  • Admin dashboards that accept campaign results or transaction logs
  • SaaS apps that connect Looker to user-generated data

📷 Example UI embed: CSVBox importer UI

🗃️ Full list of supported destinations:
CSVBox Destination Docs

Real-World Use Cases

  • 🚀 SaaS platforms letting customers sync Excel forecasts into Looker dashboards
  • 🛍️ E-commerce teams tracking promotions and uploading inventory status via spreadsheets
  • 🧑‍💼 Customer success teams importing use-case data for NPS analysis in Looker
  • 📈 Marketing teams uploading campaign KPIs for real-time reports

FAQs: Spreadsheet Uploads to Looker

Can I upload .xlsx Excel files using CSVBox?

Yes. CSVBox supports both .csv and .xlsx file formats.

What destinations can I send my spreadsheet data to?

CSVBox supports:

  • Google BigQuery
  • Amazon Redshift
  • Snowflake
  • PostgreSQL
  • Airtable
  • More listed here: CSVBox Destinations

Can I validate spreadsheet columns and formats before upload?

Absolutely. Define schema rules in the CSVBox dashboard to enforce:

  • Required fields
  • Data types (email, number, date, string)
  • Custom validations

Is CSVBox secure?

Yes. Data is sent over HTTPS, and you can customize permissions, webhooks, and data handling endpoints.

Can I customize the uploader’s look and feel?

Yes. CSVBox offers:

  • Whitelabel support
  • Theme customizations
  • UI string translations
  • Custom logos

Does CSVBox offer a free plan?

Yes. A free tier is available, with usage-based pricing tiers beyond that.

Final Thoughts

Connecting user spreadsheet uploads to Looker doesn’t need to be hard. By using CSVBox, you simplify spreadsheet ingestion, protect data quality, and speed up time-to-insight for business users.

Your users keep using Excel. You keep control over your data pipeline.

👉 Start now: Create your free CSVBox account

Looking for implementation help?

🔗 Canonical Source: https://csvbox.io/blog/import-spreadsheet-to-looker

#integrations

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